Reliability Growth Analysis.

This function performs reliability growth analysis using the Crow-AMSAA model by Crow (1975) https://apps.dtic.mil/sti/citations/ADA020296 or piecewise NHPP model by Guo et al. (2010) doi:10.1109/RAMS.2010.5448029.

Usage

rga(
  times,
  failures,
  model_type = "Crow-AMSAA",
  breaks = NULL,
  conf_level = 0.95
)

Arguments

times

A vector of cumulative failure times.

failures

A vector of the number of failures at each corresponding time in times.

model_type

The model type. Either Crow-AMSAA (default) or Piecewise NHPP with change point detection.

breaks

An optional vector of breakpoints for the Piecewise NHPP model.

conf_level

The desired confidence level, which defaults to 95%.

Value

The function returns an object of class rga that contains:

model

The fitted model object (lm or segmented).

logLik

The log-likelihood of the fitted model.

AIC

Akaike Information Criterion.

BIC

Bayesian Information Criterion.

breakpoints

Breakpoints (log scale) if applicable.

fitted_values

Fitted cumulative failures on the original scale.

lower_bounds

Lower confidence bounds (original scale).

upper_bounds

Upper confidence bounds (original scale).

betas

Estimated beta(s).

lambdas

Estimated lambda(s).

See also

Other Reliability Growth Analysis: plot.rga(), print.rga()

Examples

times <- c(100, 200, 300, 400, 500)
failures <- c(1, 2, 1, 3, 2)
result <- rga(times, failures)
print(result)
#> Reliability Growth Analysis (RGA)
#> ---------------------------------
#> Model Type: Crow-AMSAA 
#> 
#> Parameters (per segment):
#>   Beta: 0.7987 (SE = 0.0562)
#>   Lambda: 0.0269
#> 
#> Goodness of Fit:
#>   Log-likelihood: 4.78
#>   AIC: -3.55
#>   BIC: -4.72